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学生对 DeepLearning.AI 提供的 Supervised Machine Learning: Regression and Classification 的评价和反馈

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课程概述

In the first course of the Machine Learning Specialization, you will: • Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn. • Build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. In this beginner-friendly program, you will learn the fundamentals of machine learning and how to use these techniques to build real-world AI applications. This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field. This 3-course Specialization is an updated and expanded version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012. It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.) By the end of this Specialization, you will have mastered key concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start....

热门审阅

DB

May 30, 2024

Great intro to supervised learning (regression & classification). Clear explanation of sigmoid function and decision thresholds. Could benefit from examples & exploring non-linear boundaries.

AA

Apr 29, 2023

Optional Lab lot more time than mentioned without prior experience of python and libraries used. Its estimated time should be change, it's a lot more than 1 hour. Video and exercises are very good.

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5251 - Supervised Machine Learning: Regression and Classification 的 5275 个评论（共 6,053 个）

创建者 Vatsal S

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Apr 3, 2023

niceeee

创建者 Vladimir B

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Mar 26, 2023

Supper!

创建者 davidwangca

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Feb 19, 2023

Super!!

创建者 Anas H

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Feb 14, 2023

love it

创建者 Sebastian S

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Nov 19, 2022

love it

创建者 Abdelatif H

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Oct 30, 2022

Thanks

创建者 Mohammed A

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Sep 20, 2022

ممتازه

创建者 Mariam L

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Aug 30, 2022

perfect

创建者 Lasha L

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Aug 20, 2022

exelent

创建者 Motez M

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Aug 3, 2022

so good

创建者 胡金榜

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Jul 15, 2022

great!!

创建者 Seong H P

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Jul 14, 2022

Awesome

创建者 Raman C

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Jun 29, 2022

awesome

创建者 Rowan Z

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Jan 30, 2026

bravo!

创建者 Jagrut T

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Aug 10, 2025

Thanks

创建者 Hakia S

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Apr 1, 2025

使我受益良多

创建者 Κωνσταντίνα Δ

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Feb 1, 2025

Great!

创建者 Alizay Y

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Jan 1, 2025

thanks

创建者 Noor A A ( n

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Dec 20, 2024

Thanks

创建者 Marco T Á C

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Oct 24, 2024

Superb

创建者 Amit A

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Dec 14, 2023

Great.

创建者 Sarfaraz A K

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Dec 4, 2023

amaing

创建者 MRITUNJAY P

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Nov 8, 2023

Thanks

创建者 21020051 P G V A

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Sep 25, 2023

Great!

创建者 mostfa s

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Sep 4, 2023

thanks